Secure and efficient anonymization of distributed confidential databases

Abstract

Let us consider the following situation: $$t$$ t entities (e.g., hospitals) hold different databases containing different records for the same type of confidential (e.g., medical) data. They want to deliver a protected version of this data to third parties (e.g., pharmaceutical researchers), preserving in some way both the utility and the privacy of the original data. This can be done by applying a statistical disclosure control (SDC) method. One possibility is that each entity protects its own database individually, but this strategy provides less utility and privacy than a collective strategy where the entities cooperate, by means of a distributed protocol, to produce a global protected dataset. In this paper, we investigate the problem of distributed protocols for SDC protection methods. We propose a simple, efficient and secure distributed protocol for the specific SDC method of rank shuffling. We run some experiments to evaluate the quality of this protocol and to compare the individual and collective strategies for solving the problem of protecting a distributed database. With respect to other distributed versions of SDC methods, the new protocol provides either more security or more efficiency, as we discuss through the paper.